Prediction of Investor-Specific Trading Trends in South Korean Stock Markets Using a BiLSTM Prediction Model Based on Sentiment Analysis of Financial News Articles

Jae Jung Han and Hyun-jung Kim

Journal of Behavioral Finance, 2023, vol. 24, issue 4, 398-410

Abstract: Stock market performance is determined by supply and demand of individual, institutional, and foreign investors, who increasingly use media such as news articles for decision-making. We present a bidirectional long short term memory model to forecast trading trends based on statistically significant investor-specific topics from financial news datasets. The application of this study shows three valuable results: (i) topics significantly meaningful to each investor type differ, (ii) investors show different decision-making trends for the same news topics and different sensitivity levels, and (iii) news topics significantly associated with investors’ responses differ according to the stock market and sensitivity.

Date: 2023
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DOI: 10.1080/15427560.2021.1995735

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